CN106505633A - A kind of honourable access capacity determines method and device - Google Patents
A kind of honourable access capacity determines method and device Download PDFInfo
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- CN106505633A CN106505633A CN201611113911.0A CN201611113911A CN106505633A CN 106505633 A CN106505633 A CN 106505633A CN 201611113911 A CN201611113911 A CN 201611113911A CN 106505633 A CN106505633 A CN 106505633A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The invention provides a kind of honourable access capacity determines method and device, the method predefines a series of honourable access capacity mix proportion schemes, the generation of electricity by new energy for setting up every group of mix proportion scheme is exerted oneself time serieses and Load Time Series, used as the input that sequential produces simulation-optimization model；The sequential production simulation-optimization model for being target with new forms of energy receiving amount to the maximum is built, former optimization problem is formed；Former optimization problem is divided into sub- optimization problem, sub- optimization problem is solved by the period；The new forms of energy receiving amount of former optimization problem of measuring is received according to the new forms of energy of sub- optimization problem, and calculate new forms of energy ration the power supply rate；The new forms of energy of all honourable access capacity mix proportion schemes of comparison are rationed the power supply rate, determine that new forms of energy are rationed the power supply the corresponding optimum scene access capacity of minimum of rate；The device includes：Determining unit, comparing unit, computing unit and resolving cell.The technical scheme that the present invention is provided improves optimization efficiency and effect of optimization, meets the needs of engineering practicability.
Description
Technical field
The present invention relates to new forms of energy planning construction field, in particular to a kind of honourable access capacity determines method and dress
Put.
Background technology
With expanding economy and the continuous progress of society, the demand and degree of dependence of the energy are grown with each passing day, with wind, light
Headed by new forms of energy because its reserves is big, pollution-free, safety and environmental protection the characteristics of, develop very fast.By the end of the year 2015, China
Wind-powered electricity generation and photovoltaic power generation grid-connecting capacity reached 145GW and 43GW, occupy first place in the world.New forms of energy are exerted oneself with strong
Randomness and undulatory property, for some areas of developing of new forms of energy still lack scientific and reasonable planning, such as only with wind energy, the sun
Can respective resource level formulating the planning of new forms of energy capacity, this causes the electrical network and load of new energy development capacity and area
Mismatch between level, so as to cause new forms of energy access capacity to greatly exceed the acceptable ability of electrical network, some areas occur
" abandoning wind ", " abandoning light " phenomenon, some areas have exceeded 30% to the rate of rationing the power supply of new forms of energy.
The determination of regional power grid new forms of energy access capacity need to consider the normal power supplies peak modulation capacity and load water of electrical network
Flat, scientific and reasonable planning.The access capacity of wind-powered electricity generation and photovoltaic generation in electrical network carries out unified coordinated planning, reduces new
The energy is exerted oneself undulatory property, to greatest extent using and play wind energy and solar energy has good resource mutual over time and space
Characteristic is mended, resource complementation advantage is played, is effectively improved total access capacity of new forms of energy in electrical network.
The planing method of existing region new forms of energy access capacity is broadly divided into two big class：The first is bent based on typical day
The method of line, is typically based on typical sunrise force curve that wind-powered electricity generation and photovoltaic generation exert oneself or most extreme power curve determines new forms of energy
Access capacity.New forms of energy are exerted oneself with extremely strong Diurnal, and the result of calculation that different sunrise force curves is obtained is far apart not
With.Second method is the optimization method for producing simulation based on sequential, and such method is exerted oneself sequence based on the new forms of energy of long period
Row, have taken into full account undulatory property and Diurnal that new forms of energy exert oneself, the shadow of each arbitrary boundary conditions in electrical network actual motion
Ring, than more scientific and reasonable, its deficiency is that discontinuity surface quantity is big when optimizing, and required solution takes for obtained result of calculation
Long, and the operation constraint in practical power systems is extremely complex, the span data of long time scale considerably increases optimization problem
Scale, and the Optimization Solution time exponentially increase again with the number of optimized variable, this undoubtedly greatly reduces the engineering of method
Practicality.
Therefore, a kind of rapid Optimum method for solving of honourable access capacity need to be provided, is fast and accurately obtained most with meeting
The needs of excellent honourable access capacity.
Content of the invention
For meeting the needs of prior art development, the invention provides a kind of honourable access capacity determines method and apparatus.
The honourable access capacity that the present invention is provided determines method, and which thes improvement is that, methods described includes：
With the sequential production simulation-optimization model for building in advance, former optimization problem is determined；The sequential produces simulative optimization
Model is exerted oneself time serieses and Load Time Series according to the generation of electricity by new energy of the honourable access capacity mix proportion scheme for pre-building
Structure is obtained；
Former optimization problem is decomposed into sub- optimization problem, sub- optimization problem is solved by the period；
The new forms of energy receiving amount obtained by sub- optimization problem determines the new forms of energy receiving amount of former optimization problem, and calculates new energy
Source is rationed the power supply rate.
The new forms of energy of all honourable access capacity mix proportion schemes of comparison are rationed the power supply rate, determine optimum honourable access capacity.
Further, Load Time Series D (t) are obtained according to demand history processing data.
Further, generation of electricity by new energy time serieses of exerting oneself include that wind-powered electricity generation and photovoltaic generation are exerted oneself time serieses, institute
State wind-powered electricity generation generated output time serieses PwT () and photovoltaic generation are exerted oneself time serieses PvT () is respectively：
Pw(t)=Cw·w(t)；
Pv(t)=Cv·v(t)；
Wherein, installed capacity of wind-driven powerPhotovoltaic installed capacityDmax：Most
Big load level；δ：Honourable total installation of generating capacity accounts for the level of percent of peak load level；α：The honourable access capacity of setting is matched somebody with somebody
Ratio；w(t)：Normalization wind power output time serieses；v(t)：Normalization photovoltaic is exerted oneself time serieses.
Further, the sequential production simulation-optimization model is shown below：
In formula, T：Hop count during total optimization, Obj：New forms of energy are always optimizing the maximum receiving aim parameter in period T；pw(t)：t
Period wind-powered electricity generation generation optimization is exerted oneself；pv(t)：T period photovoltaic generation optimizations are exerted oneself.
Further, the constraints of the sequential production simulation-optimization model includes that following constraints optimizes at T
Will meet within period：
(1) units limits of wind-powered electricity generation and photovoltaic are shown below：
0≤pw(t)≤Pw(t)
0≤pv(t)≤Pv(t) (2)
In formula, pw(t) and pv(t)：Respectively the wind-powered electricity generation of t periods and photovoltaic optimization are exerted oneself；
(2) the operation constraint of fired power generating unit includes：
Exerting oneself for unit is shown below：
In formula, pj(t)：The optimization of j class fired power generating units is exerted oneself, j=1,2 ..., J；p jWithRespectively j classes fired power generating unit
Minimum load and EIAJ；Sj(t)：Integer variable, represents the optimization start number of units of j class fired power generating units；
On-off state is shown below：
In formula, Yj(t) and ZjT () is 0-1 integer variables, represent the startup and shutdown state of j class fired power generating units respectively:When
YjDuring (t)=1, at least one start in t period j class fired power generating units is represented；Work as YjDuring (t)=0, represent in t period j classes
Fired power generating unit is not powered on；Work as ZjDuring (t)=1, at least one shutdown in t period j class fired power generating units is represented, works as Zj(t)=
When 0, represent and do not shut down in t period j class fired power generating units；Nj：The quantity of j class units；
Minimum switching on and shutting down number of times is shown below：
In formula, SNj:Total maximum switching on and shutting down number of times for optimizing j class fired power generating units in the period；
(3) account load balancing constraints are shown below：
In formula, LiT () is the transmitted power between electrical network and the interconnection i in other regions, LiT () ＞ 0 represents other regions
To electrical network input power, LiT () ＜ 0 represents electrical network to other region outputs；M is all of interconnection quantity；
(4) interconnection security constraint is shown below：
In formula,Maximum transmission power for interconnection i；
(5) system reserve constraint is shown below：
In formula, R+And R-Represent just standby and negative standby needed for electrical network respectively, be the 5% of peak load.
Further, the division of the sub- optimization problem includes：
By whole time period { t1,t2,...,tTIt is divided into the N number of time period being shown below：
Time period Θ is solved by the periodi, i=1,2 ..., N corresponding sub- optimization problems, wherein, i-th sub- optimization problem
Optimization aim be ΘiNew forms of energy receiving amount in period is maximum, is shown below：
The constraints of i-th sub- optimization problem includes：Formula (2) formula (8), and constraints is only in period ΘiInterior
Set up；Meanwhile, the optimal solution of last optimization period of previous sub- optimization problem is used as the first of next sub- optimization problem
Begin solution.
Further, the new forms of energy receiving amount of former optimization problem is calculated as follows：
Rate η of rationing the power supply of new forms of energy is calculated as follows：
Further, optimum wind is determined according to different scene access capacities with rate η of rationing the power supply of the new forms of energy corresponding to ratio cc
Denso machine capacity CwWith photovoltaic installed capacity Cv；
Minimum new forms of energy ration the power supply the corresponding wind-powered electricity generation of rate η and photovoltaic installed capacity is optimum honourable access capacity.
A kind of honourable access capacity determining device, described device include：
Determining unit, with the sequential production simulation-optimization model for building in advance, determines former optimization problem；The sequential production
Simulation-optimization model is exerted oneself time serieses and load according to the generation of electricity by new energy of the honourable access capacity mix proportion scheme for pre-building
Time serieses build and obtain；
Former optimization problem is decomposed into sub- optimization problem by resolving cell, solves sub- optimization problem by the period；
Computing unit, the new forms of energy receiving amount obtained by sub- optimization problem determine the new forms of energy receiving amount of former optimization problem,
And calculate new forms of energy and ration the power supply rate.
Comparing unit, the new forms of energy for all honourable access capacity mix proportion schemes of comparison are rationed the power supply rate, determine optimum wind
Soft exchange capacity.
Further, described device also includes：
Modeling unit, sends out for calculating the Load Time Series of the honourable access capacity mix proportion scheme for pre-building, wind-powered electricity generation
Time serieses that electricity exerts oneself time serieses and photovoltaic generation is exerted oneself, when the wind-powered electricity generation generated output time serieses and photovoltaic generation are exerted oneself
Between sequence exert oneself time serieses for generation of electricity by new energy；According to generation of electricity by new energy exert oneself time serieses and Load Time Series build when
Sequence produces simulation-optimization model.
With immediate prior art ratio, the present invention provide technical scheme have the advantages that：
1st, the technical scheme that the present invention is provided is exerted oneself time serieses and duration of load application by the generation of electricity by new energy that pre-builds
Sequence brings then sequence production simulation-optimization model into, forms former optimization problem；Former optimization problem is divided into sub- optimization problem, by
Period solves sub- optimization problem；The new forms of energy receiving amount for measuring former optimization problem is received according to the new forms of energy of sub- optimization problem,
And calculate new forms of energy and ration the power supply rate；Calculate different scene respectively and match somebody with somebody the corresponding rate of rationing the power supply of ratio, the minimum honourable proportioning of rate of rationing the power supply is i.e.
Optimum honourable access capacity, the technical scheme faster obtain the optimum scene of electrical network with fine optimization method at times
Access capacity.
2nd, fast Optimization proposed by the present invention is by setting up the Optimized model for being target with new forms of energy receiving amount to the maximum
The new forms of energy come under the different honourable access capacities of comparison are rationed the power supply rate, it is considered to the new energy of the constraints such as unit operation and operation of power networks
Source sequential production simulation-optimization model, is split by will optimize the period, former optimization problem is decomposed into a series of being easier
The sub- optimization problem for solving, by by each sub- optimization problem of period rapid solving, realizing effectively subtracting the solution of former optimization problem
Lack the calculating time, and meet the needs of engineering practicability.
3rd, the present invention provide technical scheme using period split-run and timing optimization simulation-optimization model combine excellent
Change method, that is, taken into full account undulatory property and the Diurnal of generation of electricity by new energy, and when increasing optimization again, discontinuity surface quantity, subtracts
Lack Optimization Solution and calculated the time, improve optimization efficiency and effect of optimization.
Description of the drawings
The fast Optimization flow chart that Fig. 1 is provided for the present invention.
Specific embodiment
Below with reference to Figure of description, the technical scheme of present invention offer is discussed in detail in the way of specific embodiment.
The present invention proposes a kind of regional power grid scene access capacity that simulates that produces based on sequential by period rapid Optimum
Method.As shown in figure 1, the regional power grid scene access capacity that the present invention is provided includes by period fast Optimization：
1st, annual wind power output time serieses, photovoltaic are exerted oneself time serieses, load is exerted oneself modeling time series, and right
Wind power output time serieses and photovoltaic time serieses of exerting oneself are normalized；
History according to wind-powered electricity generation and photovoltaic generation goes out that force data obtains wind-powered electricity generation and photovoltaic is exerted oneself time serieses, according to wind-powered electricity generation and
The history installed capacity of photovoltaic is normalized to sequence of exerting oneself, and obtains normalized wind-powered electricity generation and photovoltaic is exerted oneself time serieses
W (t) and v (t)；Time serieses D (t) that force data obtains network load, the Load Time Series table are gone out according to demand history
Show the sequence of the load power value composition of not t in the same time.
2nd, determine the total access capacity of scene, a series of honourable access capacities are generated with ratio, calculate per group of scene and access and hold
Amount matches somebody with somebody the corresponding honourable access capacity of ratio；
Determine the total installation of generating capacity of wind-powered electricity generation and photovoltaic, be such as set as peak load DmaxA certain level of percent δ of level.
A series of honourable access capacity is set with ratio, per group of scene is calculated and is matched somebody with somebody the corresponding honourable installed capacity level of ratio.As worked as
When honourable proportioning is α, installed capacity of wind-driven power CwWith photovoltaic installed capacity CvRespectively：
In formula, Dmax:Peak load level；δ：Honourable total access capacity accounts for the percentage ratio of peak load level；α：Scene is matched somebody with somebody
Ratio.
3rd, choose one group of honourable access capacity and match somebody with somebody ratio, go out force data according to known normalization new forms of energy, calculate full-time
New forms of energy under section are exerted oneself sequence；
Exerted oneself time serieses according to installed capacity of wind-driven power, photovoltaic installed capacity and normalization, calculate corresponding wind-powered electricity generation and generate electricity
Exert oneself time serieses PwT () and photovoltaic generation are exerted oneself time serieses Pv(t)：
4th, build and target is to the maximum with electrical network new forms of energy receiving amount, it is considered to which new forms of energy units limits, thermal power unit operation are about
The sequential production simulation-optimization model of beam, account load balancing constraints, interconnection security constraint and system reserve constraint, wind-powered electricity generation is generated electricity
Exert oneself time serieses PwT (), photovoltaic generation are exerted oneself time serieses PvT () and Load Time Series D (t) are given birth to as new forms of energy sequential
The input data of simulation-optimization model is produced, the former optimization with the new forms of energy maximum receiving amount under all the period of time as optimization aim is formed and is asked
Topic, new forms of energy sequential production simulation-optimization model are set up as follows：
(1) object function
Sequential production simulation-optimization model is under given wind-powered electricity generation and photovoltaic installed capacity, optimizes conventional power unit and new energy
Source is exerted oneself, optimization aim be all optimize new forms of energy in period T receiving amount maximum：
Wherein, pw(t) and pvT () is respectively the optimization of wind-powered electricity generation and photovoltaic in the t periods and exerts oneself
(2) constraints
The constraints of timing optimization model includes：New forms of energy units limits, thermal power unit operation constraint, balancing the load are about
The constraint of beam, interconnection security constraint and system reserve.Concrete form is as follows：
1) new forms of energy units limits
0≤pw(t)≤Pw(t)
0≤pv(t)≤Pv(t) (4)
In formula, pw(t) and pvT () is exerted oneself for the optimization of wind-powered electricity generation and photovoltaic in the t periods, the constraint representation new forms of energy are at each
The optimization of period is exerted oneself no more than its EIAJ upper limit Pw(t) and Pv(t).
2) thermal power unit operation constraint
In this model, the fired power generating unit in the whole network is divided into J big class, the number of jth class unit is Nj, fired power generating unit
Operation constraint includes unit output constraint, on-off state constraint, minimum switching on and shutting down count constraint, specific as follows：
Unit output is constrained, between representing that the optimization of fired power generating unit is exerted oneself and needs to exert oneself in its minimum and maximum technology：
In formula, pjT () is exerted oneself for the optimization of j class fired power generating units；p jWithMinimum and maximum technology for j class fired power generating units
Exert oneself；SjT () is integer variable, represent the optimization start number of units of j class fired power generating units.On-off state is constrained：
In formula, Yj(t) and ZjT () is 0-1 integer variables, represent the startup and shutdown state of jth class fired power generating unit respectively,
Work as YjDuring (t)=1, represent that j classes fired power generating unit, at least one start of t periods, works as YjDuring (t)=0, j class fired power generating units are represented
It is not powered in the t periods；Work as ZjDuring (t)=1, represent that j classes fired power generating unit, at least one shutdown of t periods, works as Zj(t)=0
When, represent that j classes fired power generating unit was not shut down in the t periods.First equation in above formula represents every class fired power generating unit in day part
Startup and shutdown number of units be less than its unit number of units；Second equation represent synchronization per class unit at most in start or
A kind of state in shutdown.
Minimum switching on and shutting down count constraint：
In formula, SNjRepresent j classes fired power generating unit in whole maximum switching on and shutting down number of times optimized in the period.
3) account load balancing constraints
In formula, LiThe transmitted power of (t) for interconnection i between electrical network and other regions, Li(t) ＞ 0 represent other regions to
Electrical network input power, LiT () ＜ 0 represents electrical network to other region outputs；M is all of interconnection quantity.The restriction table
Show the whole network fired power generating unit, wind-powered electricity generation and photovoltaic generation exert oneself with interconnection conveying power sum should be equal with the load in electrical network.
4) interconnection security constraint
In formula,For the maximum transmission power of interconnection i, the through-put power on the constraint representation interconnection is not more than which and passes
The defeated upper limit.
5) system reserve constraint
In formula, R+And R-：Represent just standby and negative standby needed for electrical network respectively, be typically set at the 5% of peak load.
The various new forms of energy sequential that constitutes produces simulation-optimization model above, and the optimized variable in the mathematical model is：
pj(t)、pw(t)、pv(t)、Li(t)、Yj(t)、Zj(t) and Sj(t).The Optimized model is typical mixed integer optimization model,
Commercial packages Cplex direct solution can be adopted.During the optimization of the Optimized model hop count T be usually whole year, when discontinuity surface number
Amount is numerous.Now, Optimized model is huge, brings great difficulty to solution.Therefore, adopt in step 5 below
Former optimization problem is decomposed into a series of sub- optimization problem with the form of time division.
5th, former optimization problem is carried out time division, obtains a series of sub- optimization problems, then solved per height by the period
Optimization problem, the optimal solution for wherein going up last optimization period that a sub- optimization problem is obtained are asked as next height optimization
The initial solution of topic, until complete the solution of all sub- optimization problems；
First by whole time period { t1,t2,...,tTN number of time period is divided into according to the tandem of time：
So each time period Θi, i=1,2 ..., N just correspond to a sub- optimization problem, and wherein, i-th son is excellent
The optimization aim of change problem is ΘiNew forms of energy receiving amount in period is maximum, such as shown in following formula (12)：
The constraints of i-th sub- optimization problem includes：Formula (4) formula (10), and constraints is only in period ΘiInterior
Set up.The mathematical form of sub- optimization problem is identical with former optimization problem, and difference is that discontinuity surface quantity greatly reduces at that time, more holds
Easily solve.Meanwhile, the optimal solution of last optimization period of previous sub- optimization problem is used as next sub- optimization problem
Initial solution.
Then, each sub- optimization problem is solved by the period, last for wherein going up that a sub- optimization problem obtains is excellent
Change the initial solution of the optimal solution as next sub- optimization problem of period, until completing the solution of all sub- optimization problems.
6th, the new forms of energy maximum receiving amount for obtaining all sub- optimization problems is summed up, and obtains corresponding to for former optimization problem
New forms of energy maximum receiving amount, then calculate corresponding new forms of energy and ration the power supply rate；
If the new forms of energy receiving amount obtained per individual sub- optimization problem is Obji, i=1,2 ..., N, then will be excellent for all sons
The new forms of energy maximum receiving amount that change problem is obtained is summed up, and obtains the corresponding new forms of energy maximum receiving amount of former optimization problem
ObjNewly：
Then, calculate corresponding new forms of energy according to following formula to ration the power supply rate：
7th, continue to solve next group of honourable access capacity with the corresponding new forms of energy maximum receiving amount of ratio, until completing to own
Calculating of the honourable access capacity with ratio；Repeat step 3-6 in step 7, calculate different scene access capacities and match somebody with somebody ratio
Corresponding new forms of energy are rationed the power supply rate, until completing calculating of all honourable access capacities with ratio.
8th, the new forms of energy of all honourable access capacity mix proportion schemes of comparison are rationed the power supply rate, and wherein minimum new forms of energy are rationed the power supply rate η
Corresponding wind-powered electricity generation and photovoltaic installed capacity are optimum honourable access capacity.
A kind of honourable access capacity determining device, the device include：
Determining unit, with the sequential production simulation-optimization model for building in advance, determines former optimization problem；The sequential production
Simulation-optimization model is exerted oneself time serieses and load according to the generation of electricity by new energy of the honourable access capacity mix proportion scheme for pre-building
Time serieses build and obtain；
Former optimization problem is decomposed into sub- optimization problem by resolving cell, solves sub- optimization problem by the period；
Computing unit, the new forms of energy receiving amount obtained by sub- optimization problem determine the new forms of energy receiving amount of former optimization problem,
And calculate new forms of energy and ration the power supply rate.
Comparing unit, the new forms of energy for all honourable access capacity mix proportion schemes of comparison are rationed the power supply rate, determine optimum wind
Soft exchange capacity.
Modeling unit, sends out for calculating the Load Time Series of the honourable access capacity mix proportion scheme for pre-building, wind-powered electricity generation
Time serieses that electricity exerts oneself time serieses and photovoltaic generation is exerted oneself, when the wind-powered electricity generation generated output time serieses and photovoltaic generation are exerted oneself
Between sequence exert oneself time serieses for generation of electricity by new energy；According to generation of electricity by new energy exert oneself time serieses and Load Time Series build when
Sequence produces simulation-optimization model.
Those skilled in the art are it should be appreciated that embodiments herein can be provided as method, system or computer program
Product.Therefore, the application can adopt complete hardware embodiment, complete software embodiment or with reference to software and hardware in terms of reality
Apply the form of example.And, the application can be adopted in one or more computers for wherein including computer usable program code
The upper computer program that implements of usable storage medium (including but not limited to disk memory, CD-ROM, optical memory etc.) is produced
The form of product.
The application is flow process of the reference according to the method, equipment (system) and computer program of the embodiment of the present application
Figure and/or block diagram are describing.It should be understood that can be by computer program instructions flowchart and/or each stream in block diagram
Journey and/or the combination of square frame and flow chart and/or the flow process in block diagram and/or square frame.These computer programs can be provided
Instruct the processor of general purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that produced for reality by the instruction of computer or the computing device of other programmable data processing devices
The device of the function of specifying in present one flow process of flow chart or one square frame of multiple flow processs and/or block diagram or multiple square frames.
These computer program instructions may be alternatively stored in and can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory is produced to be included referring to
Make the manufacture of device, the command device realize in one flow process of flow chart or one square frame of multiple flow processs and/or block diagram or
The function of specifying in multiple square frames.
These computer program instructions can be also loaded in computer or other programmable data processing devices so that in meter
Series of operation steps is executed on calculation machine or other programmable devices to produce computer implemented process, so as in computer or
The instruction executed on other programmable devices is provided for realization in one flow process of flow chart or multiple flow processs and/or block diagram one
The step of function of specifying in individual square frame or multiple square frames.
Above example is only in order to illustrate technical scheme rather than a limitation, although reference above-described embodiment pair
The present invention has been described in detail, and those of ordinary skill in the art still can enter to the specific embodiment of the present invention
Row modification or equivalent, these any modification or equivalents without departing from spirit and scope of the invention, in application
Within the claims of the pending present invention.
Claims (10)
1. a kind of honourable access capacity determines method, it is characterised in that methods described includes：
With the sequential production simulation-optimization model for building in advance, former optimization problem is determined；The sequential produces simulation-optimization model
Exert oneself time serieses and Load Time Series of generation of electricity by new energy according to the honourable access capacity mix proportion scheme for pre-building build
Obtain；
Former optimization problem is decomposed into sub- optimization problem, sub- optimization problem is solved by the period；
The new forms of energy receiving amount obtained by sub- optimization problem determines the new forms of energy receiving amount of former optimization problem, and calculates new forms of energy limit
Electric rate；
The new forms of energy of all honourable access capacity mix proportion schemes of comparison are rationed the power supply rate, determine optimum honourable access capacity.
2. the method for claim 1, it is characterised in that Load Time Series D (t) process number according to demand history
According to obtaining.
3. the method for claim 1, it is characterised in that generation of electricity by new energy time serieses of exerting oneself include wind-powered electricity generation and light
Volt generated output time serieses, wind-powered electricity generation generated output time serieses PwT () and photovoltaic generation are exerted oneself time serieses Pv(t) point
It is not：
Pw(t)=Cw·w(t)；
Pv(t)=Cv·v(t)；
Wherein, installed capacity of wind-driven powerPhotovoltaic installed capacityMaximum negative
Lotus level；δ：Honourable total installation of generating capacity accounts for the level of percent of peak load level；α：The honourable access capacity of setting matches somebody with somebody ratio；
w(t)：Normalization wind power output time serieses；v(t)：Normalization photovoltaic is exerted oneself time serieses.
4. the method for claim 1, it is characterised in that the sequential production simulation-optimization model is shown below：
In formula, T：Hop count during total optimization；Obj：New forms of energy are always optimizing the maximum receiving aim parameter in period T；pw(t)：The t periods
Wind-powered electricity generation generation optimization is exerted oneself；pv(t)：T period photovoltaic generation optimizations are exerted oneself.
5. method as claimed in claim 4, it is characterised in that the sequential produces the constraints bag of simulation-optimization model
Include, following constraints will be met within T optimizes the period：
(1) units limits of wind-powered electricity generation and photovoltaic are shown below：
0≤pw(t)≤Pw(t)
0≤pv(t)≤Pv(t) (2)
In formula, pw(t) and pv(t)：Respectively the wind-powered electricity generation of t periods and photovoltaic optimization are exerted oneself；
(2) the operation constraint of fired power generating unit includes：
Exerting oneself for unit is shown below：
In formula, pj(t)：The optimization of j class fired power generating units is exerted oneself, j=1,2 ..., J；p jWithRespectively j classes fired power generating unit is most
Little exert oneself and EIAJ；Sj(t)：Integer variable, represents the optimization start number of units of j class fired power generating units；
On-off state is shown below：
In formula, Yj(t) and ZjT () is 0-1 integer variables, represent the startup and shutdown state of j class fired power generating units respectively:Work as Yj(t)
When=1, at least one start in t period j class fired power generating units is represented；Work as YjDuring (t)=0, represent in t period j class thermoelectricitys
Unit is not powered on；Work as ZjDuring (t)=1, at least one shutdown in t period j class fired power generating units is represented, works as ZjDuring (t)=0,
Represent and do not shut down in t period j class fired power generating units；Nj：The quantity of j class units；
Minimum switching on and shutting down number of times is shown below：
In formula, SNj:Total maximum switching on and shutting down number of times for optimizing j class fired power generating units in the period；
(3) account load balancing constraints are shown below：
In formula, LiT () is the transmitted power between electrical network and the interconnection i in other regions, LiT () ＞ 0 represents other regions to electricity
Net input power, LiT () ＜ 0 represents electrical network to other region outputs；M is all of interconnection quantity；
(4) interconnection security constraint is shown below：
In formula,Maximum transmission power for interconnection i；
(5) system reserve constraint is shown below：
In formula, R+And R-Represent just standby and negative standby needed for electrical network respectively, be the 5% of peak load.
6. the method for claim 1, it is characterised in that the division of the sub- optimization problem includes：
By whole time period { t1,t2,...,tTIt is divided into the N number of time period being shown below：
Time period Θ is solved by the periodi, i=1,2 ..., N corresponding sub- optimization problems, wherein, i-th sub- optimization problem excellent
Change target is ΘiNew forms of energy receiving amount in period is maximum, is shown below：
Meanwhile, the optimal solution of last optimization period of previous sub- optimization problem is used as the initial of next sub- optimization problem
Solution.
7. the method for claim 1, it is characterised in that new forms of energy receiving amount is calculated as follows：
Rate η of rationing the power supply of new forms of energy is calculated as follows：
8. the method for claim 1, it is characterised in that according to different scene access capacities with new corresponding to ratio cc
Energy rate η of rationing the power supply determines optimum installed capacity of wind-driven power CwWith photovoltaic installed capacity Cv；
Minimum new forms of energy ration the power supply the corresponding wind-powered electricity generation of rate η and photovoltaic installed capacity is optimum honourable access capacity.
9. a kind of honourable access capacity determining device, it is characterised in that described device includes：
Determining unit, with the sequential production simulation-optimization model for building in advance, determines former optimization problem；The sequential production simulation
Optimized model is exerted oneself time serieses and duration of load application according to the generation of electricity by new energy of the honourable access capacity mix proportion scheme for pre-building
Sequence construct is obtained；
Former optimization problem is decomposed into sub- optimization problem by resolving cell, solves sub- optimization problem by the period；
Computing unit, the new forms of energy receiving amount obtained by sub- optimization problem determine the new forms of energy receiving amount of former optimization problem, and count
Calculate new forms of energy to ration the power supply rate；
Comparing unit, the new forms of energy for all honourable access capacity mix proportion schemes of comparison are rationed the power supply rate, determine that optimum scene connects
Enter capacity.
10. device as claimed in claim 9, it is characterised in that described device also includes：
Modeling unit, generates electricity out for calculating the Load Time Series of the honourable access capacity mix proportion scheme for pre-building, wind-powered electricity generation
Power time serieses and photovoltaic generation are exerted oneself time serieses, and the wind-powered electricity generation generated output time serieses and photovoltaic generation are exerted oneself time sequence
It is classified as generation of electricity by new energy to exert oneself time serieses；Sequential life is built according to exert oneself time serieses and Load Time Series of generation of electricity by new energy
Produce simulation-optimization model.
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